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2021 IEEE Photonics Society Summer Topicals Meeting Series, SUM 2021

作者： Skontranis, Menelaos Sarantoglou, George Bogris, Adonis Mesaritakis, Charis Dept. Information and Communication Systems Engineering School of Engineering University of the Aegean Samos Greece Dept. Informatics and Computer Engineering University of West Attica Aigaleo Greece

ISBN: (纸本)9781665416009

A multi-layer photonic spiking convolutional neural network is presented, based on miniaturized VCSELs, targeting image classification. Spatial information is encoded using a time multiplexing scheme providing a radical reduction of physical neuron-count. Hardware-friendliness is enhanced by exploiting unsupervised spike-timing dependent plasticity. © 2021 IEEE.

关键词： Convolutional neural networks

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Indoor Deterministic-Based Channel Modeling at D-Band for 6G Wireless Networks

Indoor Deterministic-Based Channel Modeling at D-Band for 6G...

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IEEE Conference on Vehicular Technology (VTC)

作者： Nektarios Moraitis Demosthenes Vouyioukas School of Electrical and Computer Engineering National Technical University of Athens Athens Greece Dept. of Information and Communication Systems Engineering University of the Aegean Samos Greece

This paper presents the preliminary results of a propagation study at D-band based on deterministic modeling for an indoor line-of-sight (LOS) environment. The proposed channel model is based on multiple rays between a fixed transmitter and a moving receiver. The results reveal that the antenna characteristics significantly affect the propagation along the corridor, which is also reflected to the produced power delay profiles of the channel. Furthermore, the existence of side-corridors also influences the channel parameters, reducing the root-mean-square (rms) delay and angular spread values. At 12-m distance away from the transmitter the rms delay spread varies between 0.1 and 4.3 ns, whereas the azimuth and elevation rms angular spreads (AS) are in the range of 0.7°-12.4° and 2.1°-7.0°, respectively, depending on the selected scenario and antenna configuration.

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Self-Isolated Multiple-Input-Multiple-Output Antenna for mm-Wave Applications

Self-Isolated Multiple-Input-Multiple-Output Antenna for mm-...

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Microwave and Antenna Symposium (IMAS), International

作者： Oludayo Sokunbi Hussein Attia Abubakar Hamza Atif Shamim Ahmed A. Kishk Electrical and Computer Engineering Dept Concordia University Canada Electrical Eng. Dept Center for Communication Systems and Sensing KFUPM Saudi Arabia Computer Electrical Mathematical Science and Engineering Division KAUST Saudi Arabia

A low-cost innovative MIMO antenna configuration with minimal separation between the radiating elements and high isolation over a wide frequency band is presented. Several precisely designed slots with various forms, locations, and sizes are etched on the radiating patches to improve inter-element isolation throughout the mm-wave band of 30–41 GHz impedance bandwidth. This achieved elements isolation better than 70 dB with an inter-element spacing of 0.2 mm (0.02A at 30 GHz). The suggested self-isolation method is validated by designing a 1x2 MIMO array configuration. The innovative mm-wave antenna has the following characteristics over the desired bandwidth: high impedance bandwidth (30%) and low mutual coupling (70 dB). To the authors' knowledge, the present design is the first to demonstrate such broadband isolation enhancement in the mm-wave frequency range without any sophisticated decoupling structure such as metamaterial or frequency-selective surface.

关键词： Microwave antennas Wireless communication Surface waves Millimeter wave technology Transmitting antennas Bandwidth Impedance

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Resource Allocation in STAR-RIS-Aided SWIPT with RSMA via Meta-Learning

arXiv

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arXiv 2024年

作者： Amiri, Mojtaba Vaezpour, Elaheh Javadi, Sepideh Mili, Mohammad Robat Yanikomeroglu, Halim Bennis, Mehdi School of Electrical and Computer Engineering University of Tehran Tehran Iran Dept. of Communication ICT Research Institute Tehran Iran Tehran Iran Dept. of Systems and Computer Engineering Carleton University OttawaON Canada Centre for Wireless Communications University of Oulu Oulu Finland

Simultaneously transmitting and reflecting reconfigurable intelligent surface (STAR-RIS) is a cutting-edge concept for the sixth-generation (6G) wireless networks. In this paper, we propose a novel system that incorporates STAR-RIS with simultaneous wireless information and power transfer (SWIPT) using rate splitting multiple access (RSMA). The proposed system facilitates communication from a multi-antenna base station (BS) to single-antenna users in a downlink transmission. The BS concurrently sends energy and information signals to multiple energy harvesting receivers (EHRs) and information data receivers (IDRs) with the support of a deployed STAR-RIS. Furthermore, an optimization is introduced to strike a balance between users’ sum rate and the total harvested energy. To achieve this, an optimization problem is formulated to optimize the energy/information beamforming vectors at the BS, the phase shifts at the STAR-RIS, and the common message rate. Subsequently, we employ a meta deep deterministic policy gradient (Meta-DDPG) approach to solve the complex problem. Simulation results validate that the proposed algorithm significantly enhances both data rate and harvested energy in comparison to conventional DDPG. © 2024, CC BY.

关键词： Energy harvesting

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Cybernated Watermarking Approach on Image with Cryptographic Encryption

Cybernated Watermarking Approach on Image with Cryptographic...

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computer, communication and Control (IC4), International Conference on

作者： R. Sivasankari T Veeramakali S M Mustafa Nawaz P. Prakash P Umadevi A Alvin Ancy Dept. of Computer Science and Engineering B.S.Abdur Rahman Crescent Institute of Science and Technology Dept of Data Science and Business Systems School of Computing SRM Institute of Science and Technology Kattankulathur Tamilnadu Dept of Computer Science and Engineering Sri Sai Ram Institute of Technology Dept of Electronics and Communication Engineering Sri Sai Ram Engineering College Department of S & H KPR Institute of Engineering and Technology Coimbatore Dept of Electronics and Communication Engineering Anna University Chennai

Digital watermarking of interactive media content has become an active experimentation field in recent years. In addition to reviewing some of the methods that have been developed for various media types; a general structure for watermark engrafting and identification is outlined. We highlight a few of these application-oriented differences, including copyright protection, substantiation, tamper identification, and data hiding, as well as the technological and system conditions for different media types such as digital photos, digital files, digital audio, and text. We describe a general structure for digital watermarking-based image copyright protection in this approach. In this paper, we outline the pre-processing and implementation of tide marking technique where Twofish algorithm and double encryption is described. The image processing toolbox is also specified by comparing five different image processing techniques. In addition, the post implementation is carried out with the wavelet toolbox and matlab coder to analyze signal, image properties and generate the efficient code for embedding the text.

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AirWave: Enhancing UAV Connectivity in Cellular Networks through an Integrated Simulation Framework

AirWave: Enhancing UAV Connectivity in Cellular Networks thr...

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Big Data & Machine Learning (ICBDML), IEEE International Conference on

作者： Emirhan Zor Yusuf Taskiran Fares A. Dael Ibraheem Shayea Leila Rzayeva Zuleikha Syzdykova Electronic and Communication Engineering Istanbul Technical University Istanbul Turkey Management Information Systems İzmir Bakırçay University İzmir Turkey Dept. of Intelligent Systems and Cybersecurity Astana IT University Astana Kazakhstan Dept. of Computer Engineering Astana IT University Astana Kazakhstan

ISBN: (数字)9798350374100

ISBN: (纸本)9798350374117

This study presents AirWave, an innovative modeling framework tailored to address the challenges associated with integrating Unmanned Aerial Vehicles (UAVs) into 5G and future cellular networks. With the rising prominence of UAVs across various industries, ensuring uninterrupted connectivity and efficient mobility management within cellular networks becomes paramount. AirWave offers a comprehensive simulation environment, amalgamating network and physics simulations using ns-3 for network simulation, Gazebo for physics simulation, and integrating PX4 autopilot for realistic UAV flight dynamics. This framework facilitates in-depth investigations into UAV mobility and handover management, including a trajectory optimization technique based on reinforcement learning for cellular-connected drones. Extensive simulations demonstrate the versatility and effectiveness of AirWave, showcasing notable improvements in UAV range, connectivity, and management within cellular networks. These findings hold significant promise for advancing research and practical applications in UAV communications.

关键词： Cellular networks Reinforcement learning Propulsion Parallel processing Autonomous aerial vehicles Vehicle dynamics Physics

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Machine Learning Heart Disease Prediction Using KNN and RTC Algorithm 3

Machine Learning Heart Disease Prediction Using KNN and RTC ...

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3rd International Conference on Power, Energy, Control and Transmission systems, ICPECTS 2022

作者： Senthil, G.A. Prabha, R. Razmah, M. Veeramakali, T. Sridevi, S. Yashini, R. Agni College of Technology Dept of Information Technology Chennai India Sri Sai Ram Institute of Technology Dept of Electronics and Communication Engineering Chennai India School of Computing SRM Institute of Science and Technology Dept of Data Science and Business Systems Chennai India Sri Ramachandra Engineering and Technology Department of Computer Science and Engineering Chennai India

ISBN: (纸本)9781665462754

Heart Disease or cardiovascular disease refers to the range of heart conditions like cardiac arrest, coronary artery disease. Heart disease can be very well hindered through certain lifestyle changes. There is a significant increase in the mortality rate recently due to the distinctive heart diseases. Machine learning uses mathematical models to work efficiently with the enormous amount of data. It plays a crucial role in medical science in the prediction of distinctive diseases. Cardiologists inspects the heart functionality using electrocardiography, computed tomography. These tests are quite expensive for a common man. Recent times, the life span of a human is guaranteed only with the support of medications. As prevention is better than the cure, machine learning helps to predict the vulnerability of a heart disease with few elemental symptoms and health factors. It is been fed by the basic data of the patients like age, sex. Machine learning helps to predict the vulnerability in advance which provides the cardiologists with great acumen for the adaption of the treatment. Machine learning algorithms have proven to produce reliable and accurate output with the help of the inputs. The algorithms used in the article include KNN and decision tree classifier which is compared to yield the desired and efficient output. © 2022 IEEE.

关键词： Heart

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Mobile Gateways for LoRa End-Devices: Support Connectivity on the Move

Mobile Gateways for LoRa End-Devices: Support Connectivity o...

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IEEE International Workshop on computer-Aided Modeling, Analysis, and Design of communication Links and Networks, CAMAD

作者： Vasileios Moysiadis Dimitrios N. Skoutas Charalabos Skianis Thomas Lagkas Vasileios Argyriou Panagiotis Sarigiannidis Dept. of Electrical and Computer Engineering University of Western Macedonia Kozani Greece Dept. of Information and Communication Systems Engineering University of the Aegean Samos Greece Dept. of Computer Science International Hellenic University Greece Dept. of Networks and Digital Media Kingston University Kingston upon Thames United Kingdom

ISBN: (数字)9798350377644

ISBN: (纸本)9798350377651

This paper proposes a method enabling mobile LoRa gateways to support mobile end devices. The approach utilizes trilateration and similar approaches based on RSSI to estimate the position of end devices and specify the movement of the gateways to maintain contact. The evaluation of the proposed method tests various parameters such as speed and number of end devices, and it shows that it is able to retain contact even with speeds up to 12 mps. Moreover, the evaluation shows that the ADR-MIN algorithm performs better in this scenario than the default ADR.

关键词： Performance evaluation Network servers Conferences Computational modeling LoRa Logic gates Low-power wide area networks

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SCHEMA III: Dynamic & Scalable VNE Framework Based on Multi-Agent RL for 5G/6G Networks

SCHEMA III: Dynamic & Scalable VNE Framework Based on Multi-...

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IEEE Conference on Global communications (GLOBECOM)

作者： Anestis Dalgkitsis Luis A. Garrido Kostas Ramantas John S. Vardakas George Kormetzas Christos Verikoukis Iquadrat Informatica S.L. Barcelona Spain Information and Communication Systems Engineering Dept. University of the Aegean Samos Greece Computer Engineering & Informatics Dept. University of Patras Greece

Network Virtualization (NV) has proved a promising technology that allows multiple heterogeneous Virtual Networks (VNs) to operate simultaneously on the same infrastructure. Dynamic Virtual Network Embedding (NVE) has emerged as an enabler of elasticity and scalability in the VN deployment and resource allocation of the physical infrastructure. However, the key challenge in realizing NV in a sustainable way is how to dynamically embed VNs efficiently into physical network, which is defined as the VNE problem. To address this challenge, this paper proposes an approach that leverages Multi-Agent Reinforcement Learning (MARL) to solve the dynamic VNE of VNs for 5G/6G communication systems. The proposed framework consists of multiple horizontally distributed RL agents that co-operate to devise temporally dynamic VNE placements. The key contributions of this work are introducing a novel dynamic VNE orchestration framework for multi-domain networks based on Distributed RL, providing a scalable VNE framework targeted to Ultra-Reliable Low-Latency communication (URLLC) services, evaluating and comparing the proposed algorithm with existing solutions in the state of the art. The paper concludes that there is a significant improvement in latency of 144.191% when compared to the baselines.

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Unconventional Computing based on Four Wave Mixing in Highly Nonlinear Media

Unconventional Computing based on Four Wave Mixing in Highly...

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Conference on Lasers and Electro-Optics Europe (CLEO EUROPE)

作者： Kostas Sozos Stavros Deligiannidis Charis Mesaritakis Adonis Bogris Dept. of Informatics and Computer Engineering. Aghiou Spiridonos University of West Attica Egaleo Athens Greece Dept. of Information and Communication Systems Engineering University of the Aegean Karlovassi Samos Greece

ISBN: (纸本)9798350345995

Nowadays, photonic analog computing in the form of neuromorphic photonics or photonic neural networks has resulted in powerful hardware platforms that accelerate difficult tasks with marginal power consumption. Although linear transformations are efficiently carried out in the optical domain, nonlinear transformations are also of paramount importance. Here, we propose four wave mixing (FWM) process as an elegant solution for the generation of diverse nonlinear higher order products of an original signal. On one hand, these products can act as activation functions in different types of neural networks, either recurrent neural networks (RNNs) and reservoir computers or in any other type of brain-inspired frameworks. On the other hand, the same products can form the basis for polynomial regression which is a very powerful technique used in machine learning in different tasks i.e. for the prediction of COVID-19 transmission [1].

关键词： Four wave mixing Machine learning Neural networks Nonlinear wave mixing Optical computing Quantum computation

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